Find Academic Supervisors

Cen April Yue is an Assistant Professor of Marketing, Advertising, and Public Relations at the University of Connecticut and a Visiting Lecturer at ISM (Lithuania). She holds an Affiliate Scholar position at the Internal Communication Research Hub, University of Florida. Her research focuses on internal public relations, leadership communication, organizational change, and corporate social responsibility. She serves as Chief Research Editor at the Institute for Public Relations' Organizational Communication Research Center. Her research explores topics such as employee advocacy, CEO social media engagement, artificial intelligence in communication, and the ethical dimensions of organizational behavior. She has published extensively in journals like the Journal of Public Relations Research and Journal of Brand Management , with a focus on leadership communication strategies, internal stakeholder management, and technology-driven communication trends. Education : Not explicitly listed in provided texts. Awards : Over 10 top paper awards and recognitions from communication associations and conferences. Teaching : Courses include Public Relations (MNG229), Communication Research Methods, and Communication Campaigns. Her work bridges theoretical and practical aspects of organizational communication, emphasizing the role of technology and leadership in fostering employee relationships and managing change. Current research trends include AI's impact on internal communication and ethical challenges in corporate social responsibility.

• Internal Public Relations
• Leadership Communication
• Organizational Change Management
• +7 more

Dr. Olga Kurasova is a Professor and Senior Researcher at Vilnius University's Institute of Data Science and Digital Technologies, where she leads research in the Cognitive Computing Group. Her work focuses on developing advanced computational methods for real-world applications. Her primary research explores machine learning paradigms including deep learning for cybersecurity (keystroke dynamics, adversarial attacks), medical image analysis (pancreatic cancer detection), industrial monitoring, and explainable AI. She maintains strong collaborations across disciplines, particularly in healthcare and security domains. Analysis of her recent publications (2023-2025) reveals three dominant themes: (1) Advanced biometric authentication systems using behavioral analysis and deep learning, (2) Medical AI applications focusing on pancreatic cancer detection through CT image analysis, and (3) Theoretical advancements in explainable AI methodologies for high-stakes domains. Significant scientific recognition includes: 2021 Lithuanian Science Prize for the cycle 'From Data Science to Artificial Intelligence Technologies' 2024 Vilnius University Rector's Science Prize She has led multiple national research projects, including a 2024-2027 LMT-funded initiative on 'adversarial machine learning for cybersecurity' and coordinated interdisciplinary teams for projects on cognitive computing capabilities and optimal data mining solutions. She directs research within the Cognitive Computing Group, focusing on developing intelligent systems for data analysis, visualization, and decision support across healthcare, cybersecurity, and industrial applications.

• Machine Learning
• Data Visualization
• Cybersecurity
• +3 more

Darius Plikynas is a Senior Researcher at the Smart Technologies Research Group within the Institute of Data Science and Digital Technologies at Vilnius University . His research integrates computational intelligence methods with agent-based simulation to model cognitive and social processes. Position: Senior Researcher, Chief Researcher in the Project Address: Akademijos St. 4, room 224, Vilnius Contact: +370 5 210 9333, +370 620 95101 Email: darius.plikynas@mif.vu.lt Personal page: http://www.dariusplikynas.eu Dr. Plikynas' research spans interdisciplinary domains including neuroscience, physics methods, complexity theory, and distributed cognitive systems. He led the 2017–2019 project "Development of a metric, conceptual and simulation model of the social impact of cultural processes" under the LMT Research Group Funding Program. His recent publications (2016–2025) reflect trends in combining machine learning with social science questions (fake news analysis, propaganda detection) and agent-based modeling of cultural/social capital dynamics. Key collaborations include Leonidas Sakalauskas, Rimvydas Laužikas, and Arunas Miliauskas. Scientific supervision includes doctoral students: Andrius Budrionis (University of Tromsø, Norway) Ieva Rizgelienė (PhD topic: "Propaganda detection and classification in social media using hybrid deep learning") He also serves as an expert at Vilnius University and has contributed to projects involving: 2D financial market visualization Neural oscillation-based cognitive modeling Indoor navigation for blind individuals Cultural participation impact on social capital

• Computational Intelligence
• Agent-Based Simulation Systems
• Neuroscience
• +4 more

Kęstutis Jankauskas is an Associate Professor and Head of Department at the Faculty of Informatics , Kaunas University of Technology , Lithuania. His professional focus spans core areas within computer science and informatics. Research Interests: His work aligns with modern informatics disciplines, including but not limited to software development, data analysis, and network security. Contact: Email: kestutis.jankauskas@ktu.lt

• Computer Science
• Information Technology
• Software Engineering
• +3 more

Abdullah A. A. Ahmed is an Associate Professor in the Department of Physics at Thamar University, Yemen. He earned his Ph.D. from Universiti Putra Malaysia (UPM) in 2012 and served as a postdoctoral fellow there before returning to Yemen in 2013. He has been actively contributing to materials science research, particularly in nanomaterials, optoelectronics, energy storage, and hydrogen storage applications. Ph.D.: Universiti Putra Malaysia (UPM), 2012 Postdoctoral Fellowship: Universiti Putra Malaysia Appointment: Assistant Professor, Thamar University (2013) Promotion: Associate Professor (2019–2020) Dr. Ahmed's research spans advanced materials for energy and medical applications. His work includes the development of biopolymer electrolytes for supercapacitors, DFT studies on perovskite materials, photocatalytic nanocomposites, and nanomaterials for anticancer therapy. He frequently employs techniques such as co-precipitation, electrodeposition, and spectroscopic analysis. His recent publications (2021–2025) show a strong trend toward sustainable energy materials, including hydrogen storage in perovskite hydrides, supercapacitors using biopolymers, and photocatalytic nanocomposites for environmental remediation. There is also a growing interest in biomedical applications of nanomaterials and brain interfacing technologies. Dr. Ahmed serves as a Review Editor for Frontiers in Chemistry in the field of Medicinal and Pharmaceutical Chemistry, contributing to peer review and academic discourse. He has advised graduate students such as Annas Al-Sharabi and Ahmed Al-osta, both affiliated with Thamar University. While no specific grants are mentioned, his extensive publication record suggests active research funding and collaboration. His work is conducted within a collaborative network involving researchers from Malaysia, Saudi Arabia, India, and other international institutions, focusing on cutting-edge materials for energy, environment, and health applications.

• Materials Science
• Nanomaterials
• Optoelectronics
• +7 more

Mindaugas Bloznelis is a Professor at Vilnius University's Faculty of Mathematics and Informatics. His academic career spans decades, with active involvement in teaching and research as evidenced by his continuous presence in the university's schedules from 2016/2017 to 2025/2026. Professor Bloznelis specializes in Random Graph Theory , Network Analysis , and Probability Theory . His research focuses on connectivity thresholds, clustering coefficients, and statistical approximations in complex networks. Recent work includes advancements in modeling sparse and clustered dynamic networks, connectivity thresholds for Bernoulli random graph superpositions, and Edgeworth approximations for symmetric statistics. He co-authored the 2025 Modelling and Mining Networks workshop proceedings, highlighting his leadership in network analysis. His publications demonstrate deep expertise in stochastic processes, asymptotic theory, and finite population statistics. While no formal awards or student advisories are listed in the provided texts, his extensive publication record underscores significant contributions to probability and network science.

• Random Graph Theory
• Network Analysis
• Probability Theory
• +3 more

Dr. Vytautas Čyras serves as an Associate Professor at Vilnius University's Faculty of Mathematics and Informatics, specifically within the Institute of Computer Science and Department of Software Engineering. With over three decades of academic experience since 1984, he bridges computer science and legal theory through groundbreaking interdisciplinary research. Education: Master's in Applied Mathematics (Computer Science) from Vilnius University (1979) Doctorate from Moscow State University's Faculty of Computational Mathematics and Cybernetics (1985) Second Master's in Law from Vilnius University and German Law Centre (2007) Dr. Čyras' research spans legal informatics, information systems, and computer science. His primary focus includes artificial intelligence and law, regulatory compliance, legal requirements, and pioneering work in legal visualization. His Structural Blanks approach to programming with recurrences demonstrates deep expertise in both foundational computer science and legal applications. His research explores how visual and multisensory approaches can transform legal reasoning and compliance in digital environments. His publication trajectory reveals an evolution from technical computer science topics toward sophisticated legal informatics applications. Recent work emphasizes multisensory legal machines, legal visualization frameworks, and the integration of AI with legal reasoning systems. He has made significant contributions to understanding how legal norms can be transformed into operational rules for virtual environments and digital governance systems. Professional Activities: Active participant and organizer of major legal informatics conferences including IRIS, Baltic DB&IS, and EGOVIS Contributor to European Framework Programme projects including VirtualLife and SKY-Scanner Longstanding member of the Lithuanian Computer Society and its Intellectics Section Dr. Čyras teaches courses including Artificial Intelligence, Knowledge Representation, and Human-Computer Interaction. His interdisciplinary background enables him to bridge theoretical legal concepts with practical applications in regulatory compliance systems and legal technology development.

• Legal informatics
• Artificial intelligence and law
• Conceptualisation
• +7 more

Professor Stasys Jukna is an Affiliated Scientist at Vilnius University's Institute of Data Science and Digital Technologies, specifically within the Cybersocial Systems Engineering Group. Originally from Lithuania and identifying as a Samogitian, he maintains strong academic ties with Vilnius University while also having historical connections with Goethe University of Frankfurt and the University of Trier. His research focuses on theoretical computer science, particularly circuit complexity and combinatorics. Jukna has made significant contributions to understanding lower bounds in computational complexity, Boolean function analysis, and dynamic programming limitations. His work bridges mathematical theory with practical computational applications. Jukna has authored several influential books including Extremal Combinatorics with Applications in Computer Science (2001, 2nd ed. 2011), Boolean Function Complexity: Advances and Frontiers (2012), and Tropical Circuit Complexity: Limits of Pure Dynamic Programming (2023). His recent publications consistently explore the boundaries of computational complexity, particularly in circuit design and dynamic programming approaches. His research demonstrates a consistent trajectory examining fundamental limits in computation, with recent work focusing on tropical circuits, hazard-free implementations, and the relationship between different computational paradigms. The pattern shows increasing specialization in understanding the theoretical boundaries of dynamic programming approaches and circuit complexity. Professor Jukna has served on editorial boards including the Lithuanian Mathematical Journal and the Electronic Colloquium on Computational Complexity . His work has been supported by organizations including the German Research Foundation (DFG) and the Alexander von Humboldt Foundation. His teaching career spans multiple institutions, having taught Mathematical Logic and Discrete Mathematics at Vilnius University (1976-79/81), Combinatorics for Computer Science at the University of Trier (1996-99), and various theoretical computer science courses at Goethe University Frankfurt since 2000.

• Theoretical Computer Science
• Circuit Complexity
• Boolean Functions
• +4 more

Fernando Garcia is a Professor at the Universitat Politècnica de València , affiliated with the School of Economics and Social Sciences. His research focuses on Financial Economics, Portfolio Optimization, Risk Management, and Sustainable Finance, with a strong emphasis on Multicriteria Decision Analysis and Computational Finance. PhD in Business Administration and Management (Universitat Politècnica de València, 2005) Licenciado in Business Administration and Management (Universitat de València, 1999) Diplom. Kaufmann (Hochschule für Wirtschaft Bremen, 1998) His publications highlight trends in socially responsible investing, index tracking, and credit risk management using advanced methodologies like fuzzy logic, neural networks, and goal programming. He has collaborated extensively with researchers such as Jairo González-Bueno, Francisco Guijarro, and Javier Oliver across 21 works since 2009.

• Financial Economics
• Portfolio Optimization
• Risk Management
• +4 more

Kaklauskas Liudvikas is an Assistant Professor in the field of Informatics. His research focuses on fractal processes and the application of service theory in computer networks. He holds a Doctorate in Informatics Science and has extensive teaching experience in computer networks, system programming, and e-service evaluation models. He has contributed to projects such as the Moodle management system implementation and server preparation for educational platforms. His work is affiliated with the Research Priority Research Areas and Groups Researchers' Excellence Network (RENET), and he has been involved in national organizational reform initiatives like the 'High Objektives of National Organizational Reform' project funded under TEMPUS.

• Fractal Processes
• Computer Networks
• Service Theory Applications
• +4 more

Valiulis Gediminas serves as an Associate Professor at Vilnius University's Šiauliai Academy within the Department of Informatics Engineering. His academic career spans both engineering fundamentals and advanced environmental applications, with a pronounced shift toward bioaerosol monitoring and computer vision systems since 2018. His research interests focus on Environmental Informatics and Automatic Bioaerosol Detection , particularly developing computer vision models for pollen classification using light scattering techniques. This work bridges Environmental Science , Computer Vision , and Public Health through real-time pollen monitoring systems that serve allergy sufferers. His methodology combines fluorescent particle analysis , clustering algorithms , and sensor calibration to advance aerobiological research. Analysis of his publication trends reveals a strategic evolution: early work (2004-2012) centered on control systems engineering (granulation processes, microinverters), while recent output (2018-2024) demonstrates deep specialization in bioaerosol informatics . Key contributions include the Rapid-E particle counter validation, ozone-pollen interaction studies, and real-time pollen forecasting systems for clinical applications. His interdisciplinary approach connects atmospheric science with machine learning to solve environmental monitoring challenges. Automatic pollen recognition systems development Fluorescent bioaerosol characterization Real-time environmental data applications Computer vision for ecological monitoring While no formal advising relationships or scientific awards are documented in the source material, his collaborative research consistently involves multi-institutional teams across Lithuania and Europe. Current projects focus on enhancing bioaerosol sensor accuracy and developing clinical decision-support tools for allergy management through real-time environmental data integration.

• Environmental Informatics
• Bioaerosol Monitoring
• Computer Vision Applications
• +3 more

Viktor Medvedev is an Associate Professor and Senior Researcher at Vilnius University's Institute of Data Science and Digital Technologies, where he serves as Project Lead Researcher in the Blockchain and Quantum Technologies Group. His work focuses on the intersection of machine learning, data visualization, and cybersecurity applications. Dr. Medvedev earned his Doctor of Science in Computer Science Engineering in 2007 from Vilnius Gediminas Technical University and the Institute of Mathematics and Informatics. His doctoral research centered on 'Research on the application of feedforward neural networks for multidimensional data visualization,' establishing the foundation for his continued work in data analysis and visualization techniques. His research interests span machine learning , deep learning , data visualization , and cybersecurity applications . Specifically, he has made significant contributions to keystroke dynamics authentication , behavioral biometrics , dimensionality reduction techniques , and medical data analysis . His work often bridges theoretical computer science with practical applications in security and healthcare domains. Dr. Medvedev's publication record demonstrates a consistent trajectory of research excellence, with recent work focusing on advanced authentication systems using deep learning, pancreatic cancer detection through machine learning, and innovative approaches to data visualization. His research shows a clear evolution from foundational work in neural networks for data visualization to contemporary applications in cybersecurity and medical diagnostics. ICAISC'06 - Best Presentation Award (The 8th International Conference on Artificial Intelligence and Soft Computing) ICANNGA 2007 - Best Young Researcher Paper Award in Neural Networks DAMSS 2021, 2022, 2023 - Best Poster Awards As a Project Lead Researcher in the Blockchain and Quantum Technologies Group, Dr. Medvedev oversees research initiatives that combine cutting-edge technologies with practical applications. His work in cybersecurity has particular relevance to critical infrastructure protection, where insider threat detection using behavioral biometrics represents a significant contribution to the field.

• Machine Learning
• Deep Learning
• Neural Networks
• +8 more

Lazar Stosic is a Professor at the College of Professional Studies Educators, where he contributes to academic development and research in the intersection of technology and education. His work bridges technical disciplines with pedagogical innovation, particularly in digital learning environments. Research Interests: His primary areas include Educational Technology, Cybersecurity, Information and Communication Technology (ICT) in Education, and Computer Science Education. His research emphasizes improving educational quality through technological integration and securing digital learning platforms. The recent publications reflect a strong trend toward the application of computer science in educational contexts, especially focusing on cybersecurity awareness, AI ethics in assessment, and digital transformation challenges in academic institutions. These works span interdisciplinary domains combining technical rigor with psychological and organizational insights. Scientific Awards: No awards mentioned in the provided text. Advising and Grants: There is no explicit information regarding student advising, research grants, or funded projects. However, his editorial role in the journal "Psychology and Law" indicates scholarly leadership and peer recognition. Labs and Research Teams: No specific labs, research groups, or collaborative teams are mentioned in the available data.

• Educational Technology
• Information and Communication Technology in Education
• Cybersecurity
• +3 more

Dr. Alfredo Hernandez Sanchez is a Research Fellow at the Institute for International Relations and Political Science (TSPMI) at Vilnius University and a Senior Fellow at the Institute for Studies on the Mediterranean and the Middle East (IBEI). He holds a PhD in Political Science from Central European University and a BA in International Relations from UNAM, with expertise in Computational Social Sciences, Natural Language Processing (NLP), and Quantitative Text Analysis. His work bridges FinTech, International Political Economy, and anti-corruption research, including policy contributions for UNESCO, Transparency International, and the IADB. PhD in Political Economy, Central European University (2020) BA in International Relations, UNAM His research focuses on FinTech regulation , Big Data applications in governance, and corruption risk measurement using large-scale datasets. Current projects include the Political Economy of FinTech grant and the Water Integrity Risk Index initiative with UNESCO. Publications span Springer, Bloomsbury, and Emerald, covering topics like pandemic-era procurement ethics and defense corruption networks. Recent work highlights FinTech policy , anti-corruption metrics , and quantitative methods in political economy, with a trend toward AI-driven analysis of governance structures. He is also a Data Visualization enthusiast, contributing to the D·Viz blog and academic discourse via Bluesky. Notable affiliations include: Marie-Curie ERA Postdoctoral Fellow (Vilnius University) Research Fellow (IBEI) Contributor to UNESCO and IADB projects

• FinTech
• International Political Economy
• Computational Social Sciences
• +5 more

Assoc. Prof. Vassia Atanassova, PhD is an Associate Professor in the Bioinformatics and Mathematical Modelling Department at the Institute of Biophysics and Biomedical Engineering , Bulgarian Academy of Sciences. She holds a PhD in Informatics and Computer Sciences (2013) and has been actively contributing to generalized nets, intuitionistic fuzzy sets, and decision-making under uncertainty since 2002. Education : PhD in Informatics and Computer Sciences (2013), Institute of Information and Communication Technologies – BAS Master in Marketing (2009), University of National and World Economy Bachelor in Informatics (2004), Faculty of Mathematics and Informatics, Sofia University Her research focuses on intuitionistic fuzzy logic applications, generalized net modeling , and Wiki technologies for knowledge transfer . She has developed novel intuitionistic fuzzy operators and conducted extensive work on intercriteria analysis for complex systems. Recent publications emphasize fuzzy decision-making frameworks (2015-2019), with applications in Algorithm optimization Economic modeling Bioinformatics Medical data analysis Scientific Awards : Youngest Researcher Award 'Ivan Evstratiev Geshov' (2011) 2nd Award, VIII Youth Session of Federation of Scientific-Technical Unions (2010) She serves as Guest Editor for MDPI Mathematics and technical editor for international journals. Her teaching includes PhD-level courses on Wikipedia-based knowledge transfer and fuzzy set theory at Bulgarian universities.

• Generalized Nets
• Intuitionistic Fuzzy Sets
• Decision Making Under Uncertainty
• +3 more